32 - "Computational Precision Imaging and Medicine in Regulatory Science"
Host:
Alejandro F. Frangi
University of Leeds
Prof. Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds,
with joint appointments at the School of Computing and the School of Medicine. He directs the CISTIB Center for Computational Imaging and Simulation Technologies in Biomedicine. He is Turing Fellow of the Alan Turing Institute, Scientific Director of the Leeds Centre for HealthTech Innovation and Director of Research and Innovation of the Leed University Institute for Data Analytics.
Abstract:
Medical image analysis has grown into a matured field challenged by the progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, medical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the crossroads between and unifying the efforts behind mechanistic and phenomenological model-based imaging. Precision Imaging is characterised by being descriptive, predictive, and integrative. It captures three main directions in the effort to deal with the information deluge in imaging sciences and thus achieve wisdom from data, information, and knowledge. Precision imaging can lead to carefully and mechanistically engineered imaging biomarkers and the use of medical imaging-based computational modelling and simulation for improved regulatory science and innovation of medical products. This talk summarises and formalises our vision of Precision Imaging for Precision Medicine and highlights some connections with past research and our current focus on large-scale computational phenomics and in silico clinical trials.
